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The easysearch-client library has been updated to version 2.0.2, featuring a complete rewrite that removes legacy constraints and introduces a modern, type-safe API. This guide demonstrates how to integrate and use the new client effectively. Key Imporvements Lightweight & Fast: Unnecessary dependencies have been removed, resulting in a sm ...

In search engine architectures, compression algorithm selection presents a fundamental tradeoff dilemma: High compression ratios (e.g., best_compression/DEFLATE) reduce storage but slow query decompression Fast encoding schemes (e.g., default LZ4) accelerate queries but increase disk footprint Easysearch introduces a solution leveraging JDK 2 ...

Introduction to Enterprise Knowledge Retrieval Challenges Modern enterprises often accumulate vast amounts of internal documentation, ranging from product specifications and compliance guidelines to operational procedures and technical manuals. New employees frequently encounter a deluge of information, often struggling to locate specific detai ...

The Problem: Searchable but Invisible Data When utilizing advanced data compression features in Easysearch, such as source_reuse combined with ZSTD, developers may encounter a perplexing issue: a field is successfully indexed and can be found via search queries, yet the actual content is missing or "invisible" in the search results. C ...

Distributed search infrastructure has evolved significantly over the past two decades, largely driven by advancements in the Lucene ecosystem. However, shifting open-source licensing models and the growing requirement for localized, highly optimized search stacks have accelerated the development of alternative solutions. Easysearch emerges as a ...

In high-volume data ingestion scenarios, insufficiant capacity planning often leads to cluster instability. Common issues include: Excessive memory consumption causing Out-Of-Memory (OOM) errors and node disconnections. High CPU and memory usage degrading the performance of search queries. Increased disk I/O and network saturation affecting cl ...

Previous Overview and Introduction In our series on setting up the INFINI local environment: The first article, "Setting Up a Persistent INFINI Console and Easysearch Container Environment," explored how to use basic docker run commands to build the Console and Easysearch services step by step, with a focus on solving data persistenc ...

After migrating data between clusters, verifying document counts is often insufficient to guarantee data integrity. To perform a robust, content-level comparison betwean two Elasticsearch, Easysearch, or OpenSearch clusters, ENFINI Gateway provides a highly efficient solution for verifying that every document is identical across source and dest ...

Prerequisites Before configuring replication, ensure the following conditions are met on both the source and target clusters: Both clusters must have the cross-cluster-replication and index-management plugins installed. If the easysearch.yml configuration file on the target cluster defines custom node.roles, it must expilcitly include the remo ...

Modern enterprises increasingly require powerful search and analytics capabilities to handle growing data volumes. Easysearch emerges as an enterprise-grade search engine that enables organizations to build high-performance, scalable data retrieval systems. In today's cloud computing landscape, containerization has become the standard approach ...